Today, most industries aggregate and process large volumes of data for various business functions. In the financial services industry for example, a sizeable amount of data (information) is often required to process certain transactions. In the diagnostic industry, a sizable amount of patient data is often required to process clinical trial results. In the medical industry, a sizable amount of data is often required to process payment transactions. In all of these examples, much of this data is stored in files (or databases or web services) created by numerous applications that originate from many sources. For example, for financial services, the sources may be banks, asset managers, institutions and hedge funds to name a few. Unfortunately, the tabular data are often stored in different formats and/or organized according to different standards that is not predefined for such tabular data, e.g., not predefined as to the data location, order or names of columns, coding conventions, scaling, units and/or other differences in the manner in which the information being conveyed by the data is represented. Suffice it to say, the data are often difficult and time-consuming to process and use for their intended purpose.